Digital Being: social media and the predictive mind.

Social media is implicated today in an array of mental health concerns. While concerns around social media have become mainstream, little is known about the specific cognitive mechanisms underlying the correlations seen in these studies or why we find it so hard to stop engaging with these platforms when things obviously begin to deteriorate for us. New advances in computational neuroscience, however, are now poised to shed light on this matter. In this paper, we approach the phenomenon of social media addiction through the lens of the active inference framework. According to this framework, predictive agents like us use a 'generative model' of the world to predict our own incoming sense data and act to minimize any discrepancy between the prediction and incoming signal (prediction error). In order to live well and be able to act effectively to minimize prediction error, it is vital that agents like us have a generative model, which not only accurately reflects the regularities of our complex environment but is also flexible and dynamic and able to stay accurate in volatile and turbulent circumstances. In this paper, we propose that some social media platforms are a spectacularly effective way of warping an agent's generative model and of arresting the model's ability to flexibly track and adapt to changes in the environment. We go on to investigate cases of digital tech, which do not have these adverse effects and suggest-based on the active inference framework-some ways to understand why some forms of digital technology pose these risks, while others do not.

iBCS: 3. A Biopharmaceutics Classification System for Orally Inhaled Drug Products.

In this article, we specify for the first time a quantitative biopharmaceutics classification system for orally inhaled drugs. To date, orally inhaled drug product developers have lacked a biopharmaceutics classification system like the one developed to navigate the development of immediate release of oral medicines. Guideposts for respiratory drug discovery chemists and inhalation product formulators have been elusive and difficult to identify due to the complexity of pulmonary physiology, the intricacies of drug deposition and disposition in the lungs, and the influence of the inhalation delivery device used to deliver the drug as a respirable aerosol. The development of an inhalation biopharmaceutics classification system (iBCS) was an initiative supported by the Product Quality Research Institute (PQRI). The goal of the PQRI iBCS working group was to generate a qualitative biopharmaceutics classification system that can be utilized by inhalation scientists as a "rule of thumb" to identify desirable molecular properties and recognize and manage CMC product development risks based on physicochemical properties of the drug and the deposited lung dose. Herein, we define the iBCS classes quantitatively according to the dose number and permeability. The proposed iBCS was evaluated for its ability to categorize marketed inhaled drugs using data from the literature. The appropriateness of the classification of each drug was assessed based on published development, clinical and nonclinical data, and mechanistic physiologically based biopharmaceutics modeling. The inhaled drug product development challenges for each iBCS classification are discussed and illustrated for different classes of marketed inhaled drugs. Finally, it is recognized that discriminatory laboratory methods to characterize regional lung deposition, dissolution, and permeability will be key to fully realizing the benefits of an iBCS to streamline and derisk inhaled drug development.

Generating meaning: active inference and the scope and limits of passive AI.

Prominent accounts of sentient behavior depict brains as generative models of organismic interaction with the world, evincing intriguing similarities with current advances in generative artificial intelligence (AI). However, because they contend with the control of purposive, life-sustaining sensorimotor interactions, the generative models of living organisms are inextricably anchored to the body and world. Unlike the passive models learned by generative AI systems, they must capture and control the sensory consequences of action. This allows embodied agents to intervene upon their worlds in ways that constantly put their best models to the test, thus providing a solid bedrock that is - we argue - essential to the development of genuine understanding. We review the resulting implications and consider future directions for generative AI.

Cultivating creativity: predictive brains and the enlightened room problem.

How can one conciliate the claim that humans are uncertainty minimizing systems that seek to navigate predictable and familiar environments with the claim that humans can be creative? We call this the Enlightened Room Problem (ERP). The solution, we suggest, lies not (or not only) in the error-minimizing brain but in the environment itself. Creativity emerges from various degrees of interplay between predictive brains and changing environments: ones that repeatedly move the goalposts for our own error-minimizing machinery. By (co)constructing these challenging worlds, we effectively alter and expand the space within which our own prediction engines operate, and that function as 'exploration bubbles' that enable information seeking, uncertainty minimizing minds to penetrate deeper and deeper into artistic, scientific and engineering space. In what follows, we offer a proof of principle for this kind of environmentally led cognitive expansion. This article is part of the theme issue 'Art, aesthetics and predictive processing: theoretical and empirical perspectives'.

Differential effect of lactate on synovial fibroblast and macrophage effector functions.

Introduction: The synovial membrane is the main site of inflammation in rheumatoid arthritis (RA). Here several subsets of fibroblasts and macrophages, with distinct effector functions, have been recently identified. The RA synovium is hypoxic and acidic, with increased levels of lactate as a result of inflammation. We investigated how lactate regulates fibroblast and macrophage movement, IL-6 secretion and metabolism via specific lactate transporters. Methods: Synovial tissues were taken from patients undergoing joint replacement surgery and fulfilling the 2010 ACR/EULAR RA criteria. Patients with no evidence of degenerative or inflammatory disease were used as control. Expression of the lactate transporters SLC16A1 and SLC16A3 on fibroblasts and macrophages was assessed by immunofluorescence staining and confocal microscopy. To test the effect of lactate in vitro we used RA synovial fibroblasts and monocyte-derived macrophages. Migration was assessed via scratch test assays or using trans-well inserts. Metabolic pathways were analysed by Seahorse analyser. IL-6 secretion was determined by ELISA. Bioinformatic analysis was performed on publicly available single cell and bulk RNA sequencing datasets. Results: We show that: i) SLC16A1 and SLC16A3 which regulate lactate intake and export respectively, are both expressed in RA synovial tissue and are upregulated upon inflammation. SLC16A3 is more highly expressed by macrophages, while SLC16A1 was expressed by both cell types. ii) This expression is maintained in distinct synovial compartments at mRNA and protein level. iii) Lactate, at the concentration found in RA joints (10 mM), has opposite effects on the effector functions of these two cell types. In fibroblasts, lactate promotes cell migration, IL-6 production and increases glycolysis. In contrast macrophages respond to increases in lactate by reducing glycolysis, migration, and IL-6 secretion. Discussion: In this study, we provide the first evidence of distinct functions of fibroblasts and macrophages in presence of high lactate levels, opening new insights in understanding the pathogenesis of RA and offering novel potential therapeutic targets.

Extended active inference: Constructing predictive cognition beyond skulls.

Cognitive niche construction is the process whereby organisms create and maintain cause-effect models of their niche as guides for fitness influencing behavior. Extended mind theory claims that cognitive processes extend beyond the brain to include predictable states of the world. Active inference and predictive processing in cognitive science assume that organisms embody predictive (i.e., generative) models of the world optimized by standard cognitive functions (e.g., perception, action, learning). This paper presents an active inference formulation that views cognitive niche construction as a cognitive function aimed at optimizing organisms' generative models. We call that process of optimization extended active inference.

iBCS: 1. Principles and Framework of an Inhalation-Based Biopharmaceutics Classification System.

For oral drugs, the formulator and discovery chemist have a tool available to them that can be used to navigate the risks associated with the selection and development of immediate release oral drugs and drug products. This tool is the biopharmaceutics classification system (giBCS). Unfortunately, no such classification system exists for inhaled drugs. The perspective outlined in this manuscript provides the foundational principles and framework for a classification system for inhaled drugs. The proposed classification system, an inhalation-based biopharmaceutics classification system (iBCS), is based on fundamental biopharmaceutics principles adapted to an inhalation route of administration framework. It is envisioned that a classification system for orally inhaled drugs will facilitate an understanding of the technical challenges associated with the development of new chemical entities and their associated new drug products (device and drug formulation combinations). Similar to the giBCS, the iBCS will be based on key attributes describing the drug substance (solubility and permeability) and the drug product (dose and dissolution). This manuscript provides the foundational aspects of an iBCS, including the proposed scientific principles and framework upon which such a system can be developed.

The potential cost-effectiveness of HPV vaccination among girls in Mongolia.

Introduction: Cervical cancer is a leading cause of cancer among women in Mongolia with an age-standardized incidence rate of 23.5 per 100,000. HPV vaccination has not been introduced nationally and Gavi co-financing support is not available in Mongolia. Extended Gavi pricing for HPV vaccine may be available from vaccine manufacturers for a number of years. To inform introduction decision-making, we evaluated the potential cost-effectiveness of HPV vaccination among girls and young women in Mongolia. Methods: We used UNIVAC (version 1.4), a static decision model, to evaluate the health and economic outcomes of single-cohort vaccination among females from the government perspective compared to no vaccination. We modeled vaccine introduction over 10 birth cohorts starting in 2022 comparing quadrivalent or bivalent vaccine selection and vaccine pricing variations. We used locally-specific data for cancer incidence, mortality, treatment and costs. Model outcomes included cancer cases, hospitalizations, deaths, disability-adjusted life years (DALY), and costs presented in 2018 USD. Incremental costs and health outcomes were discounted at 3% and aggregated into an Incremental Cost-Effectiveness Ratio (ICER). Results: The base-case scenario of HPV vaccination among 9 year-old girls was projected to avert 5,692 cervical cancer cases, 3,240 deaths, and 11,886 DALYs and incur $2.4-3.1M more costs compared to no vaccination. At prices of ($4.50-$4.60/dose), we estimated an ICER of $166-$265/DALY averted among 9-year-olds. When price per dose was increased to reported mean vaccine purchase price for non-Gavi LMICs ($14.17/dose), the ICER ranged from $556-820/DALY averted. Conclusion: HPV vaccination among girls is highly likely to be a cost-effective investment in Mongolia compared to no vaccination with projected ICERs less than 20% of the 2018 GDP per capita of $3,735.

iBCS: 2. Mechanistic Modeling of Pulmonary Availability of Inhaled Drugs versus Critical Product Attributes.

This work is the second in a series of publications outlining the fundamental principles and proposed design of a biopharmaceutics classifications system for inhaled drugs and drug products (the iBCS). Here, a mechanistic computer-based model has been used to explore the sensitivity of the primary biopharmaceutics functional output parameters: (i) pulmonary fraction dose absorbed (Fabs) and (ii) drug half-life in lumen (t1/2) to biopharmaceutics-relevant input attributes including dose number (Do) and effective permeability (Peff). Results show the nonlinear sensitivity of primary functional outputs to variations in these attributes. Drugs with Do < 1 and Peff > 1 × 10-6 cm/s show rapid (t1/2 < 20 min) and complete (Fabs > 85%) absorption from lung lumen into lung tissue. At Do > 1, dissolution becomes a critical drug product attribute and Fabs becomes dependent on regional lung deposition. The input attributes used here, Do and Peff, thus enabled the classification of inhaled drugs into parameter spaces with distinctly different biopharmaceutic risks. The implications of these findings with respect to the design of an inhalation-based biopharmaceutics classification system (iBCS) and to the need for experimental methodologies to classify drugs need to be further explored.

The effect of polymer stiffness on magnetization reversal of magnetorheological elastomers.

Ultrasoft magnetorheological elastomers (MREs) offer convenient real-time magnetic field control of mechanical properties that provides a means to mimic mechanical cues and regulators of cells in vitro. Here, we systematically investigate the effect of polymer stiffness on magnetization reversal of MREs using a combination of magnetometry measurements and computational modeling. Poly-dimethylsiloxane-based MREs with Young's moduli that range over two orders of magnitude were synthesized using commercial polymers Sylgard™ 527, Sylgard 184, and carbonyl iron powder. The magnetic hysteresis loops of the softer MREs exhibit a characteristic pinched loop shape with almost zero remanence and loop widening at intermediate fields that monotonically decreases with increasing polymer stiffness. A simple two-dipole model that incorporates magneto-mechanical coupling not only confirms that micrometer-scale particle motion along the applied magnetic field direction plays a defining role in the magnetic hysteresis of ultrasoft MREs but also reproduces the observed loop shapes and widening trends for MREs with varying polymer stiffnesses.

The Acquisition of Culturally Patterned Attention Styles Under Active Inference.

This paper presents an active inference based simulation study of visual foraging. The goal of the simulation is to show the effect of the acquisition of culturally patterned attention styles on cognitive task performance, under active inference. We show how cultural artefacts like antique vase decorations drive cognitive functions such as perception, action and learning, as well as task performance in a simple visual discrimination task. We thus describe a new active inference based research pipeline that future work may employ to inquire on deep guiding principles determining the manner in which material culture drives human thought, by building and rebuilding our patterns of attention.

Dynamic Tuning of Viscoelastic Hydrogels with Carbonyl Iron Microparticles Reveals the Rapid Response of Cells to Three-Dimensional Substrate Mechanics.

Current methods to dynamically tune three-dimensional hydrogel mechanics require specific chemistries and substrates that make modest, slow, and often irreversible changes in their mechanical properties, exclude the use of protein-based scaffolds, or alter the hydrogel microstructure and pore size. Here, we rapidly and reversibly alter the mechanical properties of hydrogels consisting of extracellular matrix proteins and proteoglycans by adding carbonyl iron microparticles (MPs) and applying external magnetic fields. This approach drastically alters hydrogel mechanics: rheology reveals that application of a 4000 Oe magnetic field to a 5 mg/mL collagen hydrogel containing 10 wt % MPs increases the storage modulus from approximately 1.5 to 30 kPa. Cell morphology experiments show that cells embedded within these hydrogels rapidly sense the magnetically induced changes in ECM stiffness. Ca2+ transients are altered within seconds of stiffening or subsequent softening, and slower but still dynamic changes occur in YAP nuclear translocation in response to time-dependent application of a magnetic field. The near instantaneous change in hydrogel mechanics provides new insight into the effect of changing extracellular stiffness on both acute and chronic changes in diverse cell types embedded in protein-based scaffolds. Due to its flexibility, this method is broadly applicable to future studies interrogating cell mechanotransduction in three-dimensional substrates.

Damaged hardmen: Organized crime and the half-life of deindustrialization.

Despite frequent associations, deindustrialization features rarely in studies of organized crime, and organized crime is at best a spectral presence in studies of deindustrialization. By developing an original application of Linkon's concept of the "half-life," we present an empirical case for the symbiotic relationship between former sites of industry and the emergence of criminal markets. Based on a detailed case-study in the west of Scotland, an area long associated with both industry and crime, the paper interrogates the environmental, social, and cultural after-effects of deindustrialization at a community level. Drawing on 55 interviews with residents and service-providers in Tunbrooke, an urban community where an enduring criminal market grew in the ruins of industry, the paper elaborates the complex landscapes of identity, vulnerability, and harm that are embedded in the symbiosis of crime and deindustrialization. Building on recent scholarship, the paper argues that organized crime in Tunbrooke is best understood as an instance of "residual culture" grafted onto a fragmented, volatile criminal marketplace where the stable props of territorial identity are unsettled. The analysis allows for an extension of both the study of deindustrialization and organized crime, appreciating the "enduring legacies" of closure on young people, communal identity, and social relations in the twenty-first century.

Standardization of post-operative antimicrobials reduced exposure while maintaining good outcomes in pediatric liver transplant recipients.

Infections following orthotopic liver transplant (OLT) result in significant morbidity and mortality, warranting careful consideration of risks associated with antibiotic overuse and benefits of infection prevention. In the absence of specific guidelines for antimicrobial prophylaxis in pediatric OLT, we developed a standardized approach to post-operative (post-op) antimicrobial therapy including 48 hours of antibiotics, no vancomycin for post-op fever within the first 48 hours, and caspofungin only for certain situations. The goal was to reduce antimicrobial utilization and adverse outcomes associated with longer duration of and broader treatment while maintaining good outcomes. The impact of this standardization on antimicrobial utilization and clinical outcomes at the largest pediatric liver transplant center in the United States is described. All individuals receiving an OLT from 1/1/17-9/30/17 (N = 38) and 3/14/18-12/13/18 (N = 27) were included in the pre-intervention (PreI) and post-intervention (PostI) groups, respectively. The intervention resulted in a significant reduction in individuals receiving post-op broad-spectrum gram-negative antibiotics for >48 hours (76% PreI vs 44% PostI OLT recipients, P = .01) and post-op vancomycin use (50% PreI, vs 7.4% PostI, P < .001). There were no statistically significant differences between groups for post-op fever, positive pre-/post-operative cultures, receipt of massive transfusion, or hospital length of stay. In conclusion, following the implementation of a standardized approach to post-op prophylaxis, antimicrobial exposure was significantly reduced without affecting OLT recipient outcomes.

Magnetic field tuning of mechanical properties of ultrasoft PDMS-based magnetorheological elastomers for biological applications.

We report tuning of the moduli and surface roughness of magnetorheological elastomers (MREs) by varying applied magnetic field. Ultrasoft MREs are fabricated using a physiologically relevant commercial polymer, Sylgard™ 527, and carbonyl iron powder (CIP). We found that the shear storage modulus, Young's modulus, and root-mean-square surface roughness are increased by ~41×, ~11×, and ~11×, respectively, when subjected to a magnetic field strength of 95.5 kA m-1. Single fit parameter equations are presented that capture the tunability of the moduli and surface roughness as a function of CIP volume fraction and magnetic field strength. These magnetic field-induced changes in the mechanical moduli and surface roughness of MREs are key parameters for biological applications.

Effects of Language on Visual Perception.

Does language change what we perceive? Does speaking different languages cause us to perceive things differently? We review the behavioral and electrophysiological evidence for the influence of language on perception, with an emphasis on the visual modality. Effects of language on perception can be observed both in higher-level processes such as recognition and in lower-level processes such as discrimination and detection. A consistent finding is that language causes us to perceive in a more categorical way. Rather than being fringe or exotic, as they are sometimes portrayed, we discuss how effects of language on perception naturally arise from the interactive and predictive nature of perception.

Magneto-Driven Gradients of Diamagnetic Objects for Engineering Complex Tissues.

Engineering complex tissues represents an extraordinary challenge and, to date, there have been few strategies developed that can easily recapitulate native-like cell and biofactor gradients in 3D materials. This is true despite the fact that mimicry of these gradients may be essential for the functionality of engineered graft tissues. Here, a non-traditional magnetics-based approach is developed to predictably position naturally diamagnetic objects in 3D hydrogels. Rather than magnetizing the objects within the hydrogel, the magnetic susceptibility of the surrounding hydrogel precursor solution is enhanced. In this way, a range of diamagnetic objects (e.g., polystyrene beads, drug delivery microcapsules, and living cells) are patterned in response to a brief exposure to a magnetic field. Upon photo-crosslinking the hydrogel precursor, object positioning is maintained, and the magnetic contrast agent diffuses out of the hydrogel, supporting long-term construct viability. This approach is applied to engineer cartilage constructs with a depth-dependent cellularity mirroring that of native tissue. These are thought to be the first results showing that magnetically unaltered cells can be magneto-patterned in hydrogels and cultured to generate heterogeneous tissues. This work provides a foundation for the formation of opposing magnetic-susceptibility-based gradients within a single continuous material.

Wilding the predictive brain.

The Predictive Processing (PP) framework casts the brain as a probabilistic prediction engine that continually generates predictions of the causal structure of the world in order to construct for itself, from the top down, incoming sensory signals. Conceiving of the brain in this way has yielded incredible explanatory power, offering what many believe to be our first glimpse at a unified theory of the mind. In this paper, the picture of the mind brought into view by predictive processing theories is shown to be embodied, deeply affective and nicely poised for cognitive extension. We begin by giving an overview of the main themes of the framework, and situating this approach within embodied cognitive science. We show perception, action, homeostatic regulation and emotion to be underpinned by the very same predictive machinery. We conclude by showing how predictive minds will increasingly be understood as deeply interwoven with, and perhaps extended into, the surrounding social, cultural and technological landscape. This article is categorized under: Philosophy > Foundations of Cognitive Science Psychology > Emotion and Motivation Philosophy > Action.